Class

org.apache.spark

ShuffleDependency

Related Doc: package spark

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class ShuffleDependency[K, V, C] extends Dependency[Product2[K, V]]

:: DeveloperApi :: Represents a dependency on the output of a shuffle stage. Note that in the case of shuffle, the RDD is transient since we don't need it on the executor side.

Annotations
@DeveloperApi()
Source
Dependency.scala
Linear Supertypes
Dependency[Product2[K, V]], Serializable, Serializable, AnyRef, Any
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Inherited
  1. ShuffleDependency
  2. Dependency
  3. Serializable
  4. Serializable
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Visibility
  1. Public
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Instance Constructors

  1. new ShuffleDependency(_rdd: RDD[_ <: Product2[K, V]], partitioner: Partitioner, serializer: Serializer = SparkEnv.get.serializer, keyOrdering: Option[Ordering[K]] = None, aggregator: Option[Aggregator[K, V, C]] = None, mapSideCombine: Boolean = false)(implicit arg0: ClassTag[K], arg1: ClassTag[V], arg2: ClassTag[C])

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    _rdd

    the parent RDD

    partitioner

    partitioner used to partition the shuffle output

    serializer

    Serializer to use. If not set explicitly then the default serializer, as specified by spark.serializer config option, will be used.

    keyOrdering

    key ordering for RDD's shuffles

    aggregator

    map/reduce-side aggregator for RDD's shuffle

    mapSideCombine

    whether to perform partial aggregation (also known as map-side combine)

Value Members

  1. final def !=(arg0: Any): Boolean

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    AnyRef → Any

  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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    AnyRef → Any

  4. val aggregator: Option[Aggregator[K, V, C]]

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    map/reduce-side aggregator for RDD's shuffle

  5. final def asInstanceOf[T0]: T0

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    Any

  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )

  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

  10. final def getClass(): Class[_]

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  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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  13. val keyOrdering: Option[Ordering[K]]

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    key ordering for RDD's shuffles

  14. val mapSideCombine: Boolean

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    whether to perform partial aggregation (also known as map-side combine)

  15. final def ne(arg0: AnyRef): Boolean

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    AnyRef

  16. final def notify(): Unit

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    AnyRef

  17. final def notifyAll(): Unit

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  18. val partitioner: Partitioner

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    partitioner used to partition the shuffle output

  19. def rdd: RDD[Product2[K, V]]

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    Definition Classes
    ShuffleDependency → Dependency

  20. val serializer: Serializer

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    Serializer to use.

    Serializer to use. If not set explicitly then the default serializer, as specified by spark.serializer config option, will be used.

  21. val shuffleHandle: ShuffleHandle

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  22. val shuffleId: Int

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  23. final def synchronized[T0](arg0: ⇒ T0): T0

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  24. def toString(): String

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  25. final def wait(): Unit

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    @throws( ... )

  26. final def wait(arg0: Long, arg1: Int): Unit

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    @throws( ... )

  27. final def wait(arg0: Long): Unit

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Inherited from Dependency[Product2[K, V]]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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